The present invention generally relates to methods and systems for characterizing filtration media so as to predict its key performance characteristics. The marketplace for filter products is driven today by the need to more efficient filters with increased dust holding capacity at lower pressure drop. The materials selection and construction of the filter media go a long way to determining eventual filter performance. Key parameters of the fibrous media are porosity and fiber diameter distribution. To optimize filter media performance, today's filter media is a combination of layers with different fiber diameter and/or porosity.
The enhanced performance of filter media is on the one hand achieved by combining different filter media layers, but on the other hand by optimizing the mixture of fiber diameters within one layer. Traditionally cellulose based papers are used as fibrous filters. Cellulose based papers derived from different varieties of wood offer various fiber sizes and shapes. Cellulose paper, however, is a natural product, with all its inherent fluctuation of properties and its limit of minimum fiber diameter. Another filter media material is synthetic non-woven media, which is a highly technical product offering many more parameters to control product quality and properties, e.g. smaller fibers. Consequently, a trend is developing to add synthetic media to or on top of cellulose or even shifting to fully synthetic filter media.
It is well known that the fiber diameter size predetermines particle collection efficiency. However, classical filtration theory does not account for fiber diameter distribution to calculate filtration media performance or pressure drop. As classical filtration theory is based on the single fiber approach, performance can only be predicted for an isolated single fiber diameter. The common approach to overcoming this issue by integrating over different classes of a distribution works for particle diameters, but not for fiber diameters, as “the flow field and collection efficiency associated with each fiber size are influenced by the presence of fibers of other sizes. As a practical matter, the effective fiber diameter, based on pressure drop measurement [ . . . ] is a reasonable approximation” (Hinds 1999).
A common way of determining the fiber diameter distribution in a filter media is to have an operator count the fiber diameters, for example as shown in a scanning electron microscope (SEM) image of the filter media sample. This is a very tedious task and the quality of the measured result depends on the operator. Therefore, automatic image processing has been investigated. Pourdeyhimi and Dent (1999) derived fiber diameter distribution from images by an algorithm using the skeleton and distance transformed image. Talbot et al. (2000) determined fiber diameters by automatic image analysis of cross sectional SEM images fibers. To obtain the fiber cross sections, the fibers had first to be embedded in resin and then cross sections had to be cut. This method is still time consuming. Ghassemieh et al. (2002) applied Fast Fourier Transforms (FFT) to SEM image date to obtain a fiber diameter distribution. Luzhansky (2003) presented an automatic image processing of SEM image based on an algorithm that first finds the pores in a segmented picture and then zigzags around the perimeter of a pore, jumping to the border of the adjacent pore and back by moving forward. Zibari et al. (2007) presented a method to obtain fiber diameter distribution based on binary images. To overcome the problem of methods being based on skeletons, they deleted the fiber intersections. Zibari et al. published (2008) another paper validating their method on simulated structures and comparing the result with data manually measured on SEM images of gold sputtered fibers.
Unfortunately, the past methods of determining the fiber diameter distribution of a filter media have disadvantages. Published or otherwise known methods either generate excessive amounts of data or are too sophisticated using techniques such as fast Fourier transforms (FFT) to allow for a quick and easy judgment of the quality of the fiber diameter sizing. None of the known image processing methods have been found satisfactory to be considered a practical standard way of accomplishing the task. As a result, even today filtration media fiber diameters are commonly counted (manually) by operators such as from SEM images or other known techniques.